Title: Logical Reasoning in Reinforcement Learning: A Boon or Bane?
Time: Friday, September 20, 3:00 PM
Location: CSIP library (room 5126), 5th floor, Centergy one building
Bio: Suguman Bansal is an Assistant Professor in the School of Computer Science at Georgia Institute of Technology. Her research is focused on formal methods and their applications to artificial intelligence, programming languages, and machine learning. Previously, she was an NSF/CRA Computing Innovation Postdoctoral Fellow at the University of Pennsylvania, mentored by Prof. Rajeev Alur. She completed her Ph.D. at Rice University, advised by Prof. Moshe Y. Vardi. She is the recipient of the 2020 NSF CI Fellowship, has been named a 2021 MIT EECS Rising Star, and was a keynote speaker at the 29th Static Analysis Symposium (SAS) 2022.
Abstract: Reinforcement Learning (RL) is being touted to revolutionize the way we design systems. However, a key challenge to reaching that holy grail comes from the lack of guarantees that the synthesized systems offer. Logic and formal reasoning can address some of these issues, or can they? In this talk, I will cover recent progress in using logical specifications in RL and discuss the challenges it faces moving forward.